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极化干涉合成孔径雷达(PolInSAR)测量是一种集极化雷达(PolSAR)和干涉雷达(InSAR)测量技术于一体的新的对地观测技术,利用极化干涉雷达数据提取地表植被垂直结构参数是当前极化干涉研究的热点问题。然而现在国内外适用于PolInSAR处理的数据都是重复轨道数据,其中应用广泛的是SIR-C/X-SAR数据,其成像时间在10多年前,成像区域植被高度及衰减系数大小无法考证,因此利用该数据进行反演,反演结果的精度无法验证,故有必要对极化干涉数据进行模拟来验证PolInSAR反演算法的优劣。提出了一种便于验证反演算法的基于散射体模型的PolInSAR数据模拟方法,并利用基于统计特征的反演算法验证了该数据的有效性。
Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) is a new earth observation technique integrating PolSAR and InSAR measurement technology. Polarimetric interference radar data is used to extract vertical structural parameters of surface vegetation It is a hot issue in current polarization interference research. However, at present, data suitable for PolInSAR processing both at home and abroad are repetitive orbit data. Among them, SIR-C / X-SAR data are widely used. Imaging time is more than 10 years ago. Therefore, the vegetation height and attenuation coefficient in the imaging area can not be verified. Using this data for inversion, the accuracy of inversion results can not be verified, so it is necessary to simulate the polarization interference data to verify the advantages and disadvantages of PolInSAR inversion algorithm. A PolsSAR data simulation method based on scatterer model is proposed to validate the inversion algorithm, and the validity of the data is verified by the inversion algorithm based on statistical features.